Eric Anyung Shieh

GUARDS and PROTECT: next generation applications of security games

We provide an overview of two recent applications of security games. We describe new features and challenges introduced in the new applications.

A Deployed Quantal Response-Based Patrol Planning System for the U.S. Coast Guard

In this paper, we describe the model, theory developed, and deployment of PROTECT, a game-theoretic system that the United States Coast Guard USCG uses to schedule patrols in the Port of Boston. The USCG evaluated PROTECTs deployment in the Port of Boston as a success and is currently evaluating the system in the Port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker-defender Stackelberg game model; however, its development and implementation required both theoretical contributions and detailed evaluations. We describe the work required in the deployment, which we group into five key innovations. First, we propose a compact representation of the defenders strategy space by exploiting equivalence and dominance, to make PROTECT efficient enough to solve real-world sized problems. Second, this system does not assume that adversaries are perfectly rational, a typical assumption in previous game-theoretic models for security. Instead, PROTECT relies on a quantal response QR model of the adversarys behavior. We believe this is the first real-world deployment of a QR model. Third, we develop specialized solution algorithms that can solve this problem for real-world instances and give theoretical guarantees. Fourth, our experimental results illustrate that PROTECTs QR model handles real-world uncertainties more robustly than a perfect-rationality model. Finally, we present 1 a comparison of human-generated and PROTECT security schedules, and 2 results of an evaluation of PROTECT from an analysis by human mock attackers.

PROTECT -- A Deployed Game Theoretic System for Strategic Security Allocation for the United States Coast Guard

While three deployed applications of game theory for security have recently been reported, we as a community of agents and AI researchers remain in the early stages of these deployments; there is a continuing need to understand the core principles for innovative security applications of game theory. Towards that end, this paper presents PROTECT, a game-theoretic system deployed by the United States Coast Guard (USCG) in the port of Boston for scheduling their patrols. USCG has termed the deployment of PROTECT in Boston a success, and efforts are underway to test it in the port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker-defender Stackelberg game model and offers five key innovations. First, this system is a departure from the assumption of perfect adversary rationality noted in previous work, relying instead on a quantal response (QR) model of the adversarys behavior --- to the best of our knowledge, this is the first real-world deployment of the QR model. Second, to improve PROTECTs efficiency, we generate a compact representation of the defenders strategy space, exploiting equivalence and dominance. Third, we show how to practically model a real maritime patrolling problem as a Stackelberg game. Fourth, our experimental results illustrate that PROTECTs QR model more robustly handles real-world uncertainties than a perfect rationality model. Finally, in evaluating PROTECT, this paper for the first time provides real-world data: (i) comparison of human-generated vs PROTECT security schedules, and (ii) results from an Adversarial Perspective Teams (human mock attackers) analysis.

Unleashing Dec-MDPs in security games: enabling effective defender teamwork

Multiagent teamwork and defender-attacker security games are two areas that are currently receiving significant attention within multiagent systems research. Unfortunately, despite the need for effective teamwork among multiple defenders, little has been done to harness the teamwork research in security games. This paper is the first to remedy this situation by integrating the powerful teamwork mechanisms offered by Dec-MDPs into security games. We offer the following novel contributions in this paper: (i) New models of security games where a defender teams pure strategy is defined as a Dec-MDP policy for addressing coordination under uncertainty; (ii) New algorithms based on column generation that enable efficient generation of mixed strategies given this new model; (iii) Handling global events during defender execution for effective teamwork; (iv) Exploration of the robustness of randomized pure strategies. The paper opens the door to a potentially new area combining computational game theory and multiagent teamwork.

An extended study on addressing defender teamwork while accounting for uncertainty in attacker defender games using iterative Dec-MDPs

Multi-agent teamwork and defender-attacker security games are two areas that are currently receiving significant attention within multi-agent systems research. Unfortunately, despite the need for effective teamwork among multiple defenders, little has been done to harness the teamwork

Security Games in the Field: Deployments on a Transit System

This paper proposes the Multi-Operation Patrol Scheduling System (MOPSS), a new system to generate patrols for transit system. MOPSS is based on five contributions. First, MOPSS is the first system to use three fundamentally different adversary models for the threats of fare evasion, terrorism and crime, generating three significantly different types of patrol schedule. Second, to handle uncertain interruptions in the execution of patrol schedules, MOPSS uses Markov decision processes (MDPs) in its scheduling. Third, MOPSS is the first system to account for joint activities between multiple resources, by employing the well known SMART security game model that tackles coordination between defender’s resources. Fourth, we are also the first to deploy a new Opportunistic Security Game model, where the adversary, a criminal, makes opportunistic decisions on when and where to commit crimes. Our fifth, and most important, contribution is the evaluation of MOPSS via real-world deployments, providing data from security games in the field.

PROTECT in the Ports of Boston, New York and Beyond: Experiences in Deploying Stackelberg Security Games with Quantal Response

The global need for security of key infrastructure with limited resources has led to significant interest in research conducted in multiagent systems towards game-theory for real-world security. As reported previously at AAMAS, three applications based on Stackelberg games have been transitioned to real-world deployment. This includes ARMOR, used by the Los Angeles International Airport to randomize checkpoints of roadways and canine patrols [16]; IRIS, which helps the US Federal Air Marshal Service [22] in scheduling air marshals on international flights; and GUARDS [17], which is under evaluation by the US Transportation Security Administration to allocate resources for airport protection. We as a community remain in the early stages of these deployments, and must continue to develop our understanding of core principles of innovative applications of game theory for security.